Abstract
The quaternion estimation (QUEST) batch attitude-determination algorithm has been extended to work in a general Kalman-e lter framework. This has been done to allow the inclusion of a complicated dynamics model and to allow the estimation of additional quantities beyond the attitude quaternion. The QUEST algorithm, which workswith vectorattitude observations, servesasa starting pointbecause itisable to work with a poor (orno)e rst guess of the attitude. This paper’ s extended version of QUEST uses square-root information e ltering techniques and linearization of the dynamics to propagate the state and its covariance. The measurement update problem is solved by a technique that is an extension of the original QUEST algorithm’ s eigenvalue/eigenvector solution. The paperdemonstrates the new algorithm’ sperformance on an attitude determination problem that usesstar-tracker and rate-gyro measurements. The new algorithm is able to converge from initial attitude errors of 180 deg and initial rate-gyro bias errors as large as 2400 deg/h.
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